Triple
T37174636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkansas attorneys |
E921004
|
entity |
| Predicate | mayBeDisciplinedFor |
P192103
|
FINISHED |
| Object | professional misconduct |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: professional misconduct | Statement: [Arkansas attorneys, mayBeDisciplinedFor, professional misconduct]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeDisciplinedFor Context triple: [Arkansas attorneys, mayBeDisciplinedFor, professional misconduct]
-
A.
regulatesDiscipline
Indicates that one entity establishes or enforces rules, standards, or controls governing the conduct or discipline of another entity.
-
B.
attractsDiscipline
Indicates a relationship where one entity draws or brings about discipline, order, or self-control in another entity.
-
C.
hasDisciplinaryApproach
Indicates that an entity employs, follows, or is characterized by a particular disciplinary method, framework, or approach.
-
D.
disciplineMayInclude
Indicates that a given discipline can encompass, involve, or contain the specified component, activity, or subfield as part of its scope.
-
E.
hasDisciplineRole
Indicates that an entity holds a specific role or function within a particular discipline or field.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69fcf36bb86c8190a0a0ccf47cb56e5c |
completed | May 7, 2026, 8:17 p.m. |
Created at: May 3, 2026, 4:15 p.m.